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Preliminary Comparison of Inverse Dynamics and Quadratic Programming control for Motion Tracking in Digital Human

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    This study compared Inverse Kinematics and Dynamics (IK-ID) with Quadratic Programming (QP) for ergonomic evaluations. QP shows promise for digital human modeling, though further refinement is needed.

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    Area of Science:

    • Biomechanics
    • Ergonomics
    • Digital Human Modeling

    Background:

    • Work-related musculoskeletal disorders are prevalent in physically demanding jobs.
    • Effective ergonomic evaluation tools are crucial for worker safety.
    • Digital Human Modeling (DHM) offers potential for assessing physical demands.

    Purpose of the Study:

    • To compare the performance of traditional Inverse Kinematics and Dynamics (IK-ID) with Quadratic Programming (QP)-based control in DHM.
    • To evaluate the accuracy of these methods in kinematic and dynamic domains during trajectory-tracing tasks.
    • To identify potential instabilities in QP control and their causes.

    Main Methods:

    • Three participants performed motion capture and force plate recorded movements.
    • IK-ID and QP control methods were applied to the recorded data.
    • Both methods were benchmarked against ground truth data for accuracy assessment.
    • A focused analysis investigated instabilities in the QP controller.

    Main Results:

    • IK-ID demonstrated superior performance compared to QP.
    • The QP approach achieved low root-mean-squared error in both kinematic and dynamic analyses.
    • QP instabilities were identified and linked to rapid, variable pelvic movements.

    Conclusions:

    • QP-based control shows potential for ergonomic evaluation in DHM.
    • Further controller refinement and validation on larger populations are necessary.
    • Understanding QP instabilities is key to improving its application in biomechanical analysis.